Leveraging consanguinity and homozygosity to identify novel recessive variants

项目摘要/摘要 全基因组关联研究(GWAS)传统上假定 遗传遗传，其中杂合基因的遗传效应完全是 介于这两种纯合基因的遗传效应之间。然而，我们知道 许多等位基因的作用方式要么是显性的，要么是隐性的。表型检测 罕见的隐性变异的影响尤其具有挑战性，因为稀有的， 纯合子基因类型。在这里，我们建议使用来自96000名个人的数据 巴基斯坦基因组资源(PGR)，以量化罕见的隐性变异对 广泛的表型性状和常见、复杂的疾病。我们的研究利用了 PGR内的高近亲交配率(这增加了稀有、 纯合子基因类型)，以及广泛的生活方式、家族史和 所有参与者。我们项目的具体目标是(1)阶段和归因于 超过96,000个PGR基因组使用一个参考小组，其中包括6,200个高- 覆盖南亚的基因组序列；(2)广泛的 表型和基因型的范围，使用标准单变量测试的组合 和新的纯合子作图方法；以及(3)推断 在PGR内的血缘关系，使用纯合子长序列的分布(导致 通过近亲婚姻)在个人内部和个人之间。

PROJECT SUMMARY/ABSTRACT Genome-wide association studies (GWAS) traditionally assume an additive model of genetic inheritance, where the genetic effect of a heterozygous genotype is exactly intermediate to the genetic effects of the two homozygous genotypes. However, we know that many alleles act in either a dominant or recessive fashion. Detecting the phenotypic effects of rare, recessive variants is especially challenging, due to the scarcity of rare, homozygous genotypes. Here, we propose to use data from 96,000 individuals from the Pakistan Genomic Resource (PGR) to quantify the effects of rare, recessive variants on a wide range of phenotypic traits and common, complex diseases. Our study leverages the high rates of inbreeding within the PGR (which increases the frequency of rare, homozygous genotypes), as well as extensive lifestyle, family history and genetic data from all participants. The specific aims for our project are (1) Phase and impute variants into more than 96,000 PGR genomes using a reference panel that includes 6,200 high- coverage genome sequences from South Asia; (2) Test for associations between a wide range of phenotypes and genotype, using a combination of standard single-variant tests and novel homozygosity-mapping approaches; and (3) Infer historical models of consanguinity within the PGR, using the distributions of long runs of homozygosity (caused by consanguineous marriages) both within and between individuals.